Using semantic relations in context-based music recommendations

Tatli I., Birtürk A.

Workshop on Music Recommendation and Discovery 2011, WOMRAD 2011, Chicago, IL, Amerika Birleşik Devletleri, 23 Ekim 2011, cilt.793, ss.14-17, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 793
  • Basıldığı Şehir: Chicago, IL
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.14-17
  • Anahtar Kelimeler: Dimensionality reduction, Recommendation systems, Semantic relations, Social tagging, User profiling
  • TED Üniversitesi Adresli: Hayır

Özet

In this paper, we describe an approach for creating music recommendations based on user-supplied tags that are augmented with a hierarchical structure extracted for top level genres from Dbpedia. In this structure, each genre is represented by its stylistic origins, typical instruments, derivative forms, sub genres and fusion genres. We use this well-organized structure in dimensionality reduction in user and item profiling. We compare two recommenders; one using our method and the other using Latent Semantic Analysis (LSA) in dimensionality reduction. The recommender using our approach outperforms the other. In addition to different dimensionality reduction methods, we evaluate the recommenders with different user profiling methods.